PerficientRemote
Lead Infrastructure Databricks Engineer with Kubernetes and AWS
United States
Full-time
6 days ago
$73,000 - $150,000 USD
H1B Sponsor Likely
Key skills
AWS Implementation ExperienceDatabricks ExpertiseInfrastructure as CodeCI/CD AutomationKubernetes OperationsDeep Technical ExpertiseAI tools proficiencyAI capabilities understandingTeam collaborationAIMLflowDatabricksAWSTerraformKubernetesJenkinsGitHub ActionsHelmIAMGitHubCI/CDLeadership
About this role
Perficient is a global AI-first consultancy that partners with innovative enterprises to deliver business results through AI. The Lead Infrastructure Databricks Engineer will lead the infrastructure engineering team, focusing on building and operating large-scale cloud platforms and CI/CD activities while collaborating with industry talent to create high-quality solutions for clients' needs.
Responsibilities:
- Lead the technical planning & requirements gathering phases including estimate, develop, test, manage projects, architect and deliver
- Serve as a technical lead and mentor. Provide technical support or leadership in the development and continual improvement of service
- Develop and maintain effective working relationships with team members
- Demonstrate the ability to adapt and work with team members of various experience level
Requirements:
- Deep Technical Expertise: 5+ years building and operating large-scale cloud platforms, with at least 2+ years in a data-focused DevOps/SRE role
- AWS Implementation Experience: Hands-on experience with AWS services (networking, IAM, security) and proven ability to manage multi-account environments
- Infrastructure as Code: Strong Terraform skills for multi-stack, multi-environment setups, applying modular design and best practices
- CI/CD Automation: Demonstrated success in building and optimizing CI/CD pipelines (GitHub Actions, Jenkins) for applications, infrastructure, and data workflows
- Must have Databricks Expertise: Practical experience with the full Databricks Lakehouse Platform, including Unity Catalog, Delta Lake, and MLflow
- Kubernetes Operations: Experience administering Kubernetes clusters—deploying workloads via kubectl and Helm, configuring observability, and troubleshooting issues
- Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support data-informed task execution
- A solid understanding of AI capabilities and limitations including ethical considerations is expected
- AWS DevOps or Solutions Architect associate/professional Certification
- Certified Kubernetes Administrator (CKA)
- Terraform Certification
- Familiarity with AI-enhanced platforms is a plus